Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals.
Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals.
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DOI：
10.1038/s41467-021-24491-0
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发表时间：
2021-07-16
影响因子：
16.6
通讯作者：
Winkler TW
中科院分区：
文献类型：
--
作者：
Stanzick KJ;Li Y;Schlosser P;Gorski M;Wuttke M;Thomas LF;Rasheed H;Rowan BX;Graham SE;Vanderweff BR;Patil SB;VA Million Veteran Program;Robinson-Cohen C;Gaziano JM;O'Donnell CJ;Willer CJ;Hallan S;Åsvold BO;Gessner A;Hung AM;Pattaro C;Köttgen A;Stark KJ;Heid IM;Winkler TW
来自全基因组关联研究（GWAS）的信号下的基因是功能研究的有希望的目标，但优先考虑变体和基因是具有挑战性的。通过对慢性肾脏病遗传学联盟和英国生物库（n = 1，201，909）中基于肌酐的估计肾小球滤过率（eGFR）进行GWAS荟萃分析，我们扩大了eGFRcrea基因座的数量（424个基因座，201个新基因座; 9.8%的eGFRcrea变异由634个独立信号变异体解释）。我们在精细映射中增加的样本量（n = 1，004，040，欧洲）使具有解析精细映射的信号数量增加了一倍以上（99%可信集下降到44个信号的1个变体，138个信号的≤5个变体）。基于胱抑素的eGFR和/或血尿素氮关联支持348个位点（分别为n = 460，826和852，678）。我们可定制的基因优先级分析工具揭示了23个引人注目的基因，包括机制见解，并能够导航可能与人类肾功能相关的基因和变异，以帮助选择实验随访的目标。在全基因组关联研究中识别因果变异和基因仍然是一个挑战，这个问题随着样本量的增加而得到改善。在这里，作者荟萃分析肾功能全基因组关联研究，以确定新的基因座和精细定位基因座，以定位参与肾功能的变异和基因。
Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up. Identifying causal variants and genes in genome-wide association studies remains a challenge, an issue that is ameliorated with larger sample sizes. Here the authors meta-analyze kidney function genome-wide association studies to identify new loci and fine-map loci to home in on variants and genes involved in kidney function.
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DOI：
10.1056/nejmoa1114248
发表时间：
2012-07-05
期刊：
The New England journal of medicine
影响因子：
--
作者：
Inker LA;Schmid CH;Tighiouart H;Eckfeldt JH;Feldman HI;Greene T;Kusek JW;Manzi J;Van Lente F;Zhang YL;Coresh J;Levey AS;CKD-EPI Investigators
通讯作者：
CKD-EPI Investigators
影响因子：
4.6
作者：
Gorski M;van der Most PJ;Teumer A;Chu AY;Li M;Mijatovic V;Nolte IM;Cocca M;Taliun D;Gomez F;Li Y;Tayo B;Tin A;Feitosa MF;Aspelund T;Attia J;Biffar R;Bochud M;Boerwinkle E;Borecki I;Bottinger EP;Chen MH;Chouraki V;Ciullo M;Coresh J;Cornelis MC;Curhan GC;d'Adamo AP;Dehghan A;Dengler L;Ding J;Eiriksdottir G;Endlich K;Enroth S;Esko T;Franco OH;Gasparini P;Gieger C;Girotto G;Gottesman O;Gudnason V;Gyllensten U;Hancock SJ;Harris TB;Helmer C;Höllerer S;Hofer E;Hofman A;Holliday EG;Homuth G;Hu FB;Huth C;Hutri-Kähönen N;Hwang SJ;Imboden M;Johansson Å;Kähönen M;König W;Kramer H;Krämer BK;Kumar A;Kutalik Z;Lambert JC;Launer LJ;Lehtimäki T;de Borst M;Navis G;Swertz M;Liu Y;Lohman K;Loos RJF;Lu Y;Lyytikäinen LP;McEvoy MA;Meisinger C;Meitinger T;Metspalu A;Metzger M;Mihailov E;Mitchell P;Nauck M;Oldehinkel AJ;Olden M;Wjh Penninx B;Pistis G;Pramstaller PP;Probst-Hensch N;Raitakari OT;Rettig R;Ridker PM;Rivadeneira F;Robino A;Rosas SE;Ruderfer D;Ruggiero D;Saba Y;Sala C;Schmidt H;Schmidt R;Scott RJ;Sedaghat S;Smith AV;Sorice R;Stengel B;Stracke S;Strauch K;Toniolo D;Uitterlinden AG;Ulivi S;Viikari JS;Völker U;Vollenweider P;Völzke H;Vuckovic D;Waldenberger M;Jin Wang J;Yang Q;Chasman DI;Tromp G;Snieder H;Heid IM;Fox CS;Köttgen A;Pattaro C;Böger CA;Fuchsberger C
通讯作者：
Fuchsberger C
影响因子：
30.8
作者：
Finucane HK;Reshef YA;Anttila V;Slowikowski K;Gusev A;Byrnes A;Gazal S;Loh PR;Lareau C;Shoresh N;Genovese G;Saunders A;Macosko E;Pollack S;Brainstorm Consortium;Perry JRB;Buenrostro JD;Bernstein BE;Raychaudhuri S;McCarroll S;Neale BM;Price AL
通讯作者：
Price AL
影响因子：
30.8
作者：
Bulik-Sullivan, Brendan K.;Loh, Po-Ru;Finucane, Hilary K.;Ripke, Stephan;Yang, Jian;Patterson, Nick;Daly, Mark J.;Price, Alkes L.;Neale, Benjamin M.
通讯作者：
Neale, Benjamin M.
遗传对人体组织基因表达的影响。
影响因子：
64.8
作者：
GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Lead analysts:;Laboratory, Data Analysis &Coordinating Center (LDACC):;NIH program management:;Biospecimen collection:;Pathology:;eQTL manuscript working group:;Battle A;Brown CD;Engelhardt BE;Montgomery SB
通讯作者：
Montgomery SB